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Jiri Kukacka

Personal Details

First Name:Jiri
Middle Name:
Last Name:Kukacka
Suffix:
RePEc Short-ID:pku316
[This author has chosen not to make the email address public]
http://ies.fsv.cuni.cz/en/staff/kukacka
Terminal Degree:2016 Institut ekonomických studií; Univerzita Karlova v Praze (from RePEc Genealogy)

Affiliation

Institut ekonomických studií
Univerzita Karlova v Praze

Praha, Czech Republic
http://ies.fsv.cuni.cz/
RePEc:edi:icunicz (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Jiri Kukacka & Erik Zila, 2024. "Wealth, Cost, and Misperception: Empirical Estimation of Three Interaction Channels in a Financial-Macroeconomic Agent-Based Model," Working Papers IES 2024/22, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2024.
  2. Lukas Petrasek & Jiri Kukacka, 2024. "US Equity Announcement Risk Premia," Working Papers IES 2024/38, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2024.
  3. Jan Sila & Evzen Kocenda & Ladislav Kristoufek & Jiri Kukacka, 2023. "Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness," Working Papers IES 2023/24, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2023.
  4. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
  5. Periklis Brakatsoulas & Jiri Kukacka, 2020. "Credit Rating Downgrade Risk on Equity Returns," Working Papers IES 2020/13, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2020.
  6. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
  7. Jiri Kukacka & Jozef Barunik, 2016. "Simulated ML Estimation of Financial Agent-Based Models," Working Papers IES 2016/07, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2016.
  8. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
  9. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  10. Jiri Kukacka & Filip Stanek, 2015. "The Impact of the Tobin Tax in a Heterogeneous Agent Model of the Foreign Exchange Market," Working Papers IES 2015/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2015.
  11. Jozef Barunik & Jiri Kukacka, 2013. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under the time-varying volatility," Papers 1302.7036, arXiv.org, revised May 2013.
  12. Jiri Kukacka & Jozef Barunik, 2012. "Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment," Papers 1205.3763, arXiv.org, revised May 2013.

Articles

  1. Proaño, Christian R. & Kukacka, Jiri & Makarewicz, Tomasz, 2024. "Belief-driven dynamics in a behavioral SEIRD macroeconomic model with sceptics," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 312-333.
  2. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
  3. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
  4. Aneta Havlinova & Jiri Kukacka, 2023. "Corporate Social Responsibility and Stock Prices After the Financial Crisis: The Role of Strategic CSR Activities," Journal of Business Ethics, Springer, vol. 182(1), pages 223-242, January.
  5. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
  6. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
  7. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
  8. Jan Polach & Jiri Kukacka, 2019. "Prospect Theory in the Heterogeneous Agent Model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 147-174, March.
  9. Filip Stanek & Jiri Kukacka, 2018. "The Impact of the Tobin Tax in a Heterogeneous Agent Model of the Foreign Exchange Market," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 865-892, April.
  10. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
  11. Jozef Barunik & Jiri Kukacka, 2015. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 959-973, June.
  12. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    2. Proaño, Christian R. & Kukacka, Jiri & Makarewicz, Tomasz, 2024. "Belief-driven dynamics in a behavioral SEIRD macroeconomic model with sceptics," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 312-333.
    3. Lux, Thomas, 2024. "Lack of identification of parameters in a simple behavioral macroeconomic model," Economics Working Papers 2024-02, Christian-Albrechts-University of Kiel, Department of Economics.

  2. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Vojtech Molnar, 2022. "Price Level Targeting with Imperfect Rationality: A Heuristic Approach," Working Papers 2022/1, Czech National Bank.
    2. Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
    3. De Grauwe, Paul & Ji, Yuemei, 2020. "Structural reforms, animal spirits and monetary policies," LSE Research Online Documents on Economics 103502, London School of Economics and Political Science, LSE Library.
    4. De Grauwe, Paul & Ji, Yuemei, 2023. "On the use of current and forward-looking data in monetary policy: a behavioural macroeconomic approach," LSE Research Online Documents on Economics 115547, London School of Economics and Political Science, LSE Library.
    5. Paul De Grauwe & Yuemei Ji, 2021. "On the Use of Current or Forward-Looking Data in Monetary Policy: A Behavioural Macroeconomic Approach," CESifo Working Paper Series 8853, CESifo.
    6. Paul De Grauwe & Yuemei Ji, 2023. "On the use of current and forward-looking data in monetary policy: a behavioural macroeconomic approach," Oxford Economic Papers, Oxford University Press, vol. 75(2), pages 526-552.

  3. Jiri Kukacka & Jozef Barunik, 2016. "Simulated ML Estimation of Financial Agent-Based Models," Working Papers IES 2016/07, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2016.

    Cited by:

    1. Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    4. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.

  4. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.

    Cited by:

    1. Steinbacher, Mitja & Raddant, Matthias & Karimi, Fariba & Camacho-Cuena, Eva & Alfarano, Simone & Iori, Giulia & Lux, Thomas, 2021. "Advances in the Agent-Based Modeling of Economic and Social Behavior," MPRA Paper 107317, University Library of Munich, Germany.
    2. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    3. Cafferata, Alessia & Tramontana, Fabio, 2022. "Disposition Effect and its outcome on endogenous price fluctuations," MPRA Paper 113904, University Library of Munich, Germany.
    4. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    5. Brianzoni, Serena & Campisi, Giovanni, 2020. "Dynamical analysis of a financial market with fundamentalists, chartists, and imitators," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).

  5. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

    Cited by:

    1. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01499344, HAL.
    2. Nils Bertschinger & Iurii Mozzhorin, 2021. "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 173-210, January.
    3. Barde, Sylvain, 2024. "Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
    4. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    5. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    6. E. Mnif & A. Jarboui & M.K. Hassan & K. Mouakhar, 2020. "Big Data Tools for Islamic Financial Analysis," Post-Print hal-04457135, HAL.
    7. Sylvain Barde, 2019. "Macroeconomic simulation comparison with a multivariate extension of the Markov Information Criterion," Studies in Economics 1908, School of Economics, University of Kent.
    8. Sylvain Barde, 2022. "Bayesian Estimation of Large-Scale Simulation Models with Gaussian Process Regression Surrogates," Studies in Economics 2203, School of Economics, University of Kent.
    9. Deborah Noguera & Gabriel Montes-Rojas, 2023. "Minskyan model with credit rationing in a network economy," SN Business & Economics, Springer, vol. 3(3), pages 1-26, March.
    10. Joel Dyer & Patrick Cannon & J. Doyne Farmer & Sebastian Schmon, 2022. "Black-box Bayesian inference for economic agent-based models," Papers 2202.00625, arXiv.org.
    11. Seri, Raffaello & Martinoli, Mario & Secchi, Davide & Centorrino, Samuele, 2021. "Model calibration and validation via confidence sets," Econometrics and Statistics, Elsevier, vol. 20(C), pages 62-86.
    12. Campiglio, Emanuele & Lamperti, Francesco & Terranova, Roberta, 2024. "Believe me when I say green! Heterogeneous expectations and climate policy uncertainty," LSE Research Online Documents on Economics 124234, London School of Economics and Political Science, LSE Library.
    13. Proaño, Christian R. & Kukacka, Jiri & Makarewicz, Tomasz, 2024. "Belief-driven dynamics in a behavioral SEIRD macroeconomic model with sceptics," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 312-333.
    14. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    15. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    16. Shiono, Takashi, 2021. "Estimation of agent-based models using Bayesian deep learning approach of BayesFlow," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    17. Mario Martinoli & Alessio Moneta & Gianluca Pallante, 2022. "Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search," LEM Papers Series 2022/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    18. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," CESifo Working Paper Series 11082, CESifo.
    19. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    20. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
    21. Filippo Gusella & Engelbert Stockhammer, 2021. "Testing fundamentalist–momentum trader financial cycles: An empirical analysis via the Kalman filter," Metroeconomica, Wiley Blackwell, vol. 72(4), pages 758-797, November.
    22. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    23. Dyer, Joel & Cannon, Patrick & Farmer, J. Doyne & Schmon, Sebastian M., 2024. "Black-box Bayesian inference for agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
    24. Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo.
    25. Siyan Chen & Saul Desiderio, 2022. "Calibration of Agent-Based Models by Means of Meta-Modeling and Nonparametric Regression," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1457-1478, December.
    26. Filippo Gusella, 2022. "Detecting and Measuring Financial Cycles in Heterogeneous Agents Models: An Empirical Analysis," Working Papers - Economics wp2022_02.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    27. Mohammad Ghaderi, 2020. "Public Health Interventions in the Face of Pandemics: Network Structure, Social Distancing, and Heterogeneity," Working Papers 1193, Barcelona School of Economics.
    28. Filippo Gusella & Giorgio Ricchiuti, 2021. "State Space Model to Detect Cycles in Heterogeneous Agents Models," Working Papers - Economics wp2021_10.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    29. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    30. Lucas Fievet & Didier Sornette, 2018. "Calibrating emergent phenomena in stock markets with agent based models," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    31. Thorsten Hens & Klaus R. Schenk‐Hoppé, 2020. "Patience Is a Virtue: In Value Investing," International Review of Finance, International Review of Finance Ltd., vol. 20(4), pages 1019-1031, December.
    32. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    33. Yanqiao Zheng & Xiaobing Zhao & Xiaoqi Zhang & Xinyue Ye & Qiwen Dai, 2019. "Mining the Hidden Link Structure from Distribution Flows for a Spatial Social Network," Complexity, Hindawi, vol. 2019, pages 1-17, May.
    34. Simone Berardi & Gabriele Tedeschi, 2016. "How banks’ strategies influence financial cycles: An approach to identifying micro behavior," Working Papers 2016/24, Economics Department, Universitat Jaume I, Castellón (Spain).
    35. Bewaji, Oluwasegun, 2024. "A computational model of bilateral credit limits in payment systems and other financial market infrastructures," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(1).
    36. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    37. Özge Dilaver & Robert Jump & Paul Levine, 2016. "Agent-based Macroeconomics and Dynamic Stochastic General Equilibrium Models: Where do we go from here?," School of Economics Discussion Papers 0116, School of Economics, University of Surrey.
    38. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    39. Tedeschi, Gabriele & Recchioni, Maria Cristina & Berardi, Simone, 2019. "An approach to identifying micro behavior: How banks’ strategies influence financial cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 329-346.
    40. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.
    41. Ghaderi, Mohammad, 2022. "Public health interventions in the face of pandemics: Network structure, social distancing, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1016-1031.
    42. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    43. Troost, Christian & Huber, Robert & Bell, Andrew R. & van Delden, Hedwig & Filatova, Tatiana & Le, Quang Bao & Lippe, Melvin & Niamir, Leila & Polhill, J. Gareth & Sun, Zhanli & Berger, Thomas, 2023. "How to keep it adequate: A protocol for ensuring validity in agent-based simulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 159, pages 1-21.
    44. Filippo Gusella, 2019. "Modelling Minskyan financial cycles with fundamentalist and extrapolative price strategies: An empirical analysis via the Kalman filter approach," Working Papers - Economics wp2019_24.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    45. Mohammad Ghaderi, 2020. "Public health interventions in the face of pandemics: network structure, social distancing, and heterogeneity," Economics Working Papers 1732, Department of Economics and Business, Universitat Pompeu Fabra.
    46. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    47. Grilli, Ruggero & Tedeschi, Gabriele & Gallegati, Mauro, 2020. "Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
    48. Serena Brianzoni & Giovanni Campisi & Graziella Pacelli, 2023. "Coexisting Attractors in a Heterogeneous Agent Model in Discrete Time," Mathematics, MDPI, vol. 11(10), pages 1-12, May.
    49. Filippo Gusella & Giorgio Ricchiuti, 2022. "A State-Space Approach for Time-Series Prediction of an Heterogeneous Agent Model," Working Papers - Economics wp2022_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.

  6. Jiri Kukacka & Filip Stanek, 2015. "The Impact of the Tobin Tax in a Heterogeneous Agent Model of the Foreign Exchange Market," Working Papers IES 2015/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2015.

    Cited by:

    1. Li, Xiao-Ping & Zhou, Chun-Yang & Tong, Bin, 2019. "Carry trades, agent heterogeneity and the exchange rate," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 343-358.
    2. Lenhard, Gregor, 2024. "Learning from the Past: The Role of Personal Experiences in Artificial Stock Markets," Working papers 2024/01, Faculty of Business and Economics - University of Basel.
    3. Xiaoping Li & Chunyang Zhou, 2024. "Tobin Tax, Carry Trade, and the Exchange Rate Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1627-1647, April.
    4. Noemi Schmitt & Ivonne Schwartz & Frank Westerhoff, 2022. "Heterogeneous speculators and stock market dynamics: a simple agent-based computational model," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1263-1282, October.
    5. Qian Zhang & Kuo-Jui Wu & Ming-Lang Tseng, 2019. "Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
    6. Li, XiaoPing & Tong, Bin & Zhou, ChunYang, 2020. "Uncertainty aversion, carry trades and agent heterogeneity in the FX market," Finance Research Letters, Elsevier, vol. 36(C).

  7. Jozef Barunik & Jiri Kukacka, 2013. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under the time-varying volatility," Papers 1302.7036, arXiv.org, revised May 2013.

    Cited by:

    1. Dennis Wesselbaum, 2017. "Catastrophe theory and the financial crisis," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(4), pages 376-391, September.
    2. Michael S. Harr'e & Adam Harris & Scott McCallum, 2019. "Singularities and Catastrophes in Economics: Historical Perspectives and Future Directions," Papers 1907.05582, arXiv.org.
    3. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    4. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    5. Michael S. Harr'e, 2018. "Multi-agent Economics and the Emergence of Critical Markets," Papers 1809.01332, arXiv.org.
    6. Wang, J., 2015. "Can a stochastic cusp catastrophe model explain housing market crashes?," CeNDEF Working Papers 15-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    7. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    8. Mohamed M. Mostafa, 2020. "Catastrophe Theory Predicts International Concern for Global Warming," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 709-731, September.
    9. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    10. Bolgorian, Meysam, 2019. "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers 2019-2, Kiel Institute for the World Economy (IfW Kiel).

  8. Jiri Kukacka & Jozef Barunik, 2012. "Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment," Papers 1205.3763, arXiv.org, revised May 2013.

    Cited by:

    1. Jia, Linlu & Ke, Jinchuan & Wang, Jun, 2019. "Volatility aggregation intensity energy futures series on stochastic finite-range exclusion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 370-383.
    2. Rodrigo Fernandes Malaquias & Gleison de Abreu Pontes, 2018. "Liquidity Restrictions on Investment Funds: Are they a Response to Behavioral Bias?," Brazilian Business Review, Fucape Business School, vol. 15(4), pages 382-390, July.
    3. Marvello Yang & Abdullah Al Mamun & Muhammad Mohiuddin & Sayed Samer Ali Al-Shami & Noor Raihani Zainol, 2021. "Predicting Stock Market Investment Intention and Behavior among Malaysian Working Adults Using Partial Least Squares Structural Equation Modeling," Mathematics, MDPI, vol. 9(8), pages 1-16, April.
    4. Heba M. Ezzat, 2019. "Disposition effect and multi-asset market dynamics," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 11(2), pages 144-164, June.
    5. da Silva, Eduardo Borges & Silva, Thiago Christiano & Constantino, Michel & Amancio, Diego Raphael & Tabak, Benjamin Miranda, 2020. "Overconfidence and the 2D:4D ratio," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    6. Yuri Biondi & Simone Righi, 2013. "What does the financial market pricing do? A simulation analysis with a view to systemic volatility, exuberance and vagary," Papers 1312.7460, arXiv.org.
    7. Suman Gupta & Vinay Goyal & Vinay Kumar Kalakbandi & Sankarshan Basu, 2018. "Overconfidence, trading volume and liquidity effect in Asia’s Giants: evidence from pre-, during- and post-global recession," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(3), pages 235-257, September.
    8. M. Fern'andez-Mart'inez & M. A S'anchez-Granero & Mar'ia Jos'e Mu~noz Torrecillas & Bill McKelvey, 2016. "A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks," Papers 1601.04188, arXiv.org.
    9. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
    10. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    11. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    12. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    13. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Ren, Fei & He, Yun-Xing, 2018. "Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 301-310.

Articles

  1. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    See citations under working paper version above.
  2. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.

    Cited by:

    1. Oluwadamilare Omole & David Enke, 2024. "Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-26, December.

  3. Aneta Havlinova & Jiri Kukacka, 2023. "Corporate Social Responsibility and Stock Prices After the Financial Crisis: The Role of Strategic CSR Activities," Journal of Business Ethics, Springer, vol. 182(1), pages 223-242, January.

    Cited by:

    1. Yiqing Tan, 2024. "Local Tournament Incentives and Corporate Social Responsibility," Journal of Business Ethics, Springer, vol. 194(1), pages 211-228, September.
    2. Huang, Jun & Li, Yun & Han, Feifei, 2024. "Walk well and talk well: Impact of the consistency of ESG performance and disclosure on firms’ stock price crash risk," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1154-1174.
    3. Nazari, Jamal A. & Poursoleyman, Ehsan, 2024. "Analysts’ recommendations on peer-relative comparable sustainability disclosure," Finance Research Letters, Elsevier, vol. 64(C).
    4. Yunhe Li & Xinyi Shen & Fang Zhang, 2024. "The effects of heterogeneous CSR on corporate stock performance: evidence from COVID-19 pandemic in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    5. Rosa Fioravante, 2024. "Beyond the Business Case for Responsible Artificial Intelligence: Strategic CSR in Light of Digital Washing and the Moral Human Argument," Sustainability, MDPI, vol. 16(3), pages 1-16, February.
    6. Emmanuel Jeffrey Dzage & György Norbert Szabados, 2024. "The Relationship of Corporate Social Responsibility with Business Performance—A Bibliometric Literature Review," Sustainability, MDPI, vol. 16(7), pages 1-25, March.

  4. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.

    Cited by:

    1. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    2. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    3. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
    4. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.

  5. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).

    Cited by:

    1. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    2. Onur Özdemir & Anoop S. Kumar, 2024. "Dynamic Efficiency and Herd Behavior During Pre- and Post-COVID-19 in the NFT Market: Evidence from Multifractal Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1255-1279, March.
    3. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Papers 2305.13123, arXiv.org.
    4. Aurelio F. Bariviera, 2020. "One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles," Papers 2003.09720, arXiv.org, revised Jun 2020.
    5. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org, revised Nov 2023.
    6. Krenar Avdulaj & Ladislav Kristoufek, 2020. "On Tail Dependence and Multifractality," Mathematics, MDPI, vol. 8(10), pages 1-13, October.
    7. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    8. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    9. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Working Papers hal-04102815, HAL.
    10. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
    11. Huang, Chuangxia & Deng, Yunke & Yang, Xiaoguang & Cao, Jinde & Yang, Xin, 2021. "A network perspective of comovement and structural change: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 76(C).
    12. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    13. Noemi Schmitt & Ivonne Schwartz & Frank Westerhoff, 2022. "Heterogeneous speculators and stock market dynamics: a simple agent-based computational model," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1263-1282, October.
    14. F. Cavalli & A. Naimzada & N. Pecora & M. Pireddu, 2021. "Market sentiment and heterogeneous agents in an evolutive financial model," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1189-1219, September.
    15. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    16. Cerruti, Gianluca & Lombardini, Simone, 2022. "Financial bubbles as a recursive process lead by short-term strategies," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 555-568.

  6. Jan Polach & Jiri Kukacka, 2019. "Prospect Theory in the Heterogeneous Agent Model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 147-174, March.
    See citations under working paper version above.
  7. Filip Stanek & Jiri Kukacka, 2018. "The Impact of the Tobin Tax in a Heterogeneous Agent Model of the Foreign Exchange Market," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 865-892, April.
    See citations under working paper version above.
  8. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    See citations under working paper version above.
  9. Jozef Barunik & Jiri Kukacka, 2015. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 959-973, June.
    See citations under working paper version above.
  10. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 12 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CMP: Computational Economics (4) 2012-05-22 2016-04-23 2021-03-08 2024-06-17
  2. NEP-ECM: Econometrics (4) 2016-04-23 2016-11-27 2018-12-24 2021-03-08
  3. NEP-ORE: Operations Research (4) 2016-07-23 2018-12-24 2020-06-08 2021-03-08
  4. NEP-FMK: Financial Markets (3) 2013-03-02 2014-12-03 2020-06-08
  5. NEP-DCM: Discrete Choice Models (2) 2018-12-24 2021-03-08
  6. NEP-FDG: Financial Development and Growth (2) 2023-08-28 2024-06-17
  7. NEP-HME: Heterodox Microeconomics (2) 2016-07-23 2024-06-17
  8. NEP-MAC: Macroeconomics (2) 2018-12-24 2021-03-08
  9. NEP-RMG: Risk Management (2) 2020-06-08 2023-08-28
  10. NEP-CBE: Cognitive and Behavioural Economics (1) 2012-05-22
  11. NEP-CWA: Central and Western Asia (1) 2021-03-08
  12. NEP-MON: Monetary Economics (1) 2023-08-28
  13. NEP-MST: Market Microstructure (1) 2014-12-03
  14. NEP-OPM: Open Economy Macroeconomics (1) 2015-12-12
  15. NEP-PAY: Payment Systems and Financial Technology (1) 2023-08-28
  16. NEP-PBE: Public Economics (1) 2015-12-12
  17. NEP-UPT: Utility Models and Prospect Theory (1) 2016-07-23

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